TL;DR

Research Engineer (AI): Developing next-generation large language models with an accent on model architecture, algorithms, and training infrastructure optimization. Focus on designing and scaling safe, steerable AI systems and conducting scientific experiments to advance understanding of large language models.

Location: Hybrid with at least 25% office presence in the UK

Salary: £250,000 - £270,000 GBP annually

Company

%hirify_global% is a public benefit corporation headquartered in San Francisco focused on creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development
Lead small research projects and collaborate on larger initiatives
Design, run, and analyze scientific experiments on large language models
Optimize and scale training infrastructure for efficiency and reliability
Develop and improve developer tooling to enhance productivity
Contribute across the stack from low-level optimizations to high-level model design

Requirements

Must have at least a Bachelor's degree or equivalent experience
Strong software engineering skills and experience with Python and deep learning frameworks (PyTorch preferred)
Familiarity with large-scale machine learning and language models
Ability to balance research goals with practical engineering constraints
Excellent communication and collaboration skills
Hybrid work policy requiring office presence at least 25% of the time
Visa sponsorship available but not guaranteed for all candidates

Nice to have

Experience with high-performance, large-scale ML systems
Knowledge of GPUs, Kubernetes, and OS internals
Experience with transformer architectures and reinforcement learning
Background in large-scale ETL processes

Culture & Benefits

Competitive compensation including equity and benefits
Generous vacation and parental leave
Flexible working hours and hybrid work environment
Inclusive and diverse workplace encouraging applications from underrepresented groups
Collaborative team culture with frequent research discussions